class_docstr: A Pandas DataFrame
  representing a matrix (e.g. a Document-Term-Matrix).
  Every cell value is one entry in the matrix.
  For example,
  `pd.DataFrame([[1, 2, 3], [4,5,6]], columns=["word1", "word2", "word3"]))`.
class_docstr_tok: ["A","Pandas","DataFrame","representing","a","matrix","(","e.g",".","a","Document-Term-Matrix",")",".","Every","cell","value","is","one","entry","in","the","matrix",".","For","example",",","`","pd.DataFrame","(","[","[","1",",","2",",","3","]",",","[","4,5,6","]","]",",","columns=","[","``","word1","''",",","``","word2","''",",","``","word3","''","]",")",")","`","."]
docstr: Check if a given Pandas Series has the properties of a DataFrame.
docstr_tok: ["Check","if","a","given","Pandas","Series","has","the","properties","of","a","DataFrame","."]
code: def check_type(df: pd.DataFrame, input_output="") -> Tuple[bool, str]:
      """
      Check if a given Pandas Series has the properties of a DataFrame.
      """
  
      error_string = (
          "should be DataFrame: The input should be a Pandas DataFrame"
          " representing a matrix, where every cell is one entry of the matrix."
          " See help(hero.HeroTypes) for more information."
      )
  
      if not isinstance(df, pd.DataFrame):
          return False, error_string
      else:
          return True, ""
  
file_path: texthero/texthero/_types.py
imports: import functools
  import pandas
  from typing import Tuple
label_desc: Use image node_id 1 for calling the DataFrame obj's underlying member method code with example usage: obj.check_type(df, input_output) and returns: False,  error_string, True,  str